Data Analyst

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Must-Have:

● 4+ / 5+ years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.

● SQL, Pyspark, Python with Banking Domain knowledge - Credit & Lending.

Working knowledge / experience of Big Data frameworks like Hadoop, Hive and Spark.

● Hands-on experience in query languages like HQL or SQL (Spark SQL) for Data exploration.

● Data mapping: Determine the data mapping required to join multiple data sets together across multiple sources.

● Documentation - Data Mapping, Subsystem Design, Technical Design, Business Requirements.

● Exposure to Logical to Physical Mapping, Data Processing Flow to measure the consistency, etc.

● Data Asset design / build: Working with the data model / asset generation team to identify critical data elements and determine the mapping for reusable data assets.

● Understanding of ER Diagram and Data Modelling concepts

● Exposure to Data quality validation

● Exposure to Data Management, Data Cleaning and Data Preparation

● Exposure to Data Schema analysis.

● Exposure to working in Agile framework.

● Knowledge of Credit Risk Frameworks such as Basel II, III, IFRS 9 and Stress Testing and understanding their drivers - advantageous

Must-Have:

● 4-6 years of professional experience as a Data Analyst with good decision-making, analytical and problem-solving skills.